A communications network is a highly complex structure of a large number of interconnected nodes of different types, wherein vast amounts of signaling and user data can be routed on a multitude of different transmission paths. In order to ensure that the capacity of the communications network can live up to the transmission expectations of its users, while keeping equipment costs at a reasonable level, methods of estimating the number of nodes required in order to support a specified traffic behavior, or a specified traffic load in an area, are desired. Such estimates can be useful when dimensioning a new communications system, as well as in a process of adjusting the capacity of an existing communications network to changing demands.
Existing methods for dimensioning of communications networks typically use numerical models to numerically calculate the desired network characteristics and thereby assist the network planning engineer during the design process. Examples of such methods are given in Chapter 8 of “WCDMA for UMTS”, edited by H. Holma and A. Toskala, John Wiley & Sons, Ltd, 2004, as well as in “Radio Network Dimensioning and Planning for WiMAX Networks”, Upaso et al., Fujitsu Sci. Tech. J, Vol. 42, 4, p. 435-450.
Such numerical dimensioning models are typically very complex, and often depend on assumptions made of the physical properties of the system to be dimensioned, of the behaviour of the users of the network, and, in particular in case of radio based communications networks, of the geographical surroundings of the network. Since the quality of the numerical model determines the consistency and applicability of the obtained results to the dimensioning of real world networks, such a numerical model needs to be as precise as possible. However, due to the complexity of these systems, it's very difficult to obtain the desired precision. No matter how precise the planning and optimization approach is, if an imprecise modeling is used, the results will be useless.